Child care has become the norm for young children in the United States. In
1995, 59 percent of children who were 5 years or younger were in nonparental
care arrangements on a regular basis (Hofferth, Shauman, Henke, and West,
1998). This care typically began at early ages and lasted substantial hours:
with 44 percent of infants under the age of 1 year were in nonparental care
for an average of 31 hours a week. In the late preschool years, 84 percent
of 4- to 5-year-olds were recorded as being in child care for an average
of 28 hours per week. The use of nonparental care in the United States is
expected to grow even further as welfare reform is fully implemented (Vandell,
1998).

It is within this framework of widespread and early-age use that questions
about child care quality have been raised. Among child care researchers,
the established view is that child care quality contributes to childrens
developmental outcomes, higher quality care being associated with better
developmental outcomes and poorer quality care being associated with poorer
outcomes for children (Clarke-Stewart and Fein, 1983; Phillips, 1987). This
view is reflected in Michael Lambs (1998) comprehensive critique of
child care research that was published in the Handbook of Child
Psychology. Lamb concluded, based on extant research, that:

Quality day care from infancy clearly has positive effects on
childrens intellectual, verbal, and cognitive development, especially
when children would otherwise experience impoverished and relatively
unstimulating home environments. Care of unknown quality may have deleterious
effects. (p. 104)

A similar conclusion was drawn in a review prepared for the Rockefeller
Foundation (Love, Schochet, and Meckstroth, 1996):

The preponderance of evidence supports the conclusion of a substantial
positive relationship between child care quality and child well-being. Evidence
for this relationship encompasses multiple dimensions of quality and diverse
indicators of childrens well-being. (p. 3)

Widely varying qualities of child care have been shown to have only
small effects on childrens concurrent development and no demonstrated
long term impact, except for disadvantaged children. (p. 95)

A major goal of the current report is to evaluate the research evidence from
which these claims and counterclaims are drawn. We then analyze the argument
for public intervention to improve the quality of child care, especially
for children from lower income-families.

A careful review of the literature indicates that reviewers often draw on
the same research studies, but interpret findings differently. These different
interpretations are based, in part, on where the reviewers have set
the bar. Some researchers place more weight on studies that include
observational assessments of child care quality and that measure psychological
processes using multiple strategies (NICHD Early Child Care Research Network,
1994). These same investigators tend to place less emphasis on the necessity
of large, nationally representative samples. Although the investigators believe
that it is important to assess and control for selection biases, they worry
more about overcontrol than undercontrol in their analyses. In contrast,
others (see Besharov, 2000; Blau, 1999c, in press) have emphasized the importance
of large, nationally representative samples and the need to have sufficient
controls in the statistical analyses. These investigators have placed greater
credence on information obtained from nationally representative surveys,
even if studies lacked observational assessments of child care quality or
objective measures of child performance.

An additional factor contributing to different conclusions about child care
quality is how heavily reviewers weigh the importance of concurrent vs. long-term
findings. As can be seen on Tables 1,
2, and 3, the research
literature describing concurrent associations between child care quality
and child performance is larger and findings are more consistent than the
research literature that tests for longer-term effects. A number of factors
may contribute to the more mixed picture for long-term effects, including
measurement problems and lack of control for experiences during the intervening
period. A better consensus about realistic and reasonable expectations about
effect sizes also is needed (McCartney & Rosenthal, in press).

Thus, a variety of factors must be considered if we are to determine whether
associations between child care quality and childrens developmental
outcomes are large enough for parents, researchers, and policy makers to
care about, and whether effects warrant public or private expenditures to
improve quality. In an effort to address these broad issues, we pose five
specific questions:

A critical issue in evaluating the research evidence is consideration of
how child care quality is measured. Researchers have measured quality in
various ways: by observing process, by recording structural and caregiver
characteristics, by assessing health and safety provisions. Child care processes
refer to actual experiences that occur in child care settings, including
childrens interactions with caregivers and peers and their participation
in different activities. Sometimes process measures are global scores that
combine experiences across several areas that include health and safety
provisions, interactions with caregivers, and age-appropriate materials.
Other process measures target specific activities or experiences, such as
language stimulation by caregivers. Structural and caregiver characteristics
refer to features such as child:adult ratio, group class size, caregiver
formal education, and caregiver specialized training related to children.
Structural and caregiver characteristics are conceptualized as more distal
indicators of child care quality. Health and safety provisions refer to both
health-promoting practices, such as hand-washing, and safety in the classroom
and on playgrounds.

Process Quality

One well-known process measure is the Early Care Environment Rating Scale
(ECERS, Harms and Clifford, 1980). This measure is composed of 37 items that
evaluate seven aspects of center-based care for children ages two and a half
to five years. These areas are personal care routines, furnishings, language
reasoning experiences, motor activities, creative activities, social development,
and staff needs. Detailed descriptors are provided for each item and each
item is rated as inadequate (1), minimal (3), good (5), and excellent (7).
The ratings, according to the scale developers, are based on a minimum of
a two-hour block of observation in the classroom. The Infant/Toddler Environment
Rating Scale (ITERS, Harms, Cryer, and Clifford, 1990) is a related measure
that assesses process quality in centers for children younger than two and
a half years. The 35 items of the ITERS also are organized under seven domains
and are rated on 7-point scales.

These same investigators have developed a 32-item observational measure,
the Family Day Care Rating Scale (FDCRS), to assess process quality in child
care homes (Harms and Clifford, 1989). Some items parallel items on the ITERS
and the ECERS, but other items are unique because the instrument tries
to remain realistic for family day care home settings by not requiring that
things be done as they are in day care centers (p. 1).

As can be seen on Tables 1,
2, and 3, these measures
are used widely in child care research. The measures have important strengths,
including having good psychometric properties and being relatively easy to
use reliably. Their widespread use means that cross-study comparisons are
possible. These measures also have some limitations. The global composite
score combines features of the physical environment, social experiences,
and working conditions for staff. Some of these areas may well have greater
influences on childrens intellectual functioning or social-emotional
well-being than others. The composite score may underestimate effects relative
to more targeted scales. A second limitation is that these measures are
setting-specific. As a result, they cannot be used as interchangeable measures
of quality, meaning that it is not possible to make simple comparisons across
types of care or to combine scores in omnibus analyses that look at quality
effects across different types of care. A third limitation is that these
measures are not appropriate for assessing in-home care given by nannies
or grandparents.

The Observational Record of the Caregiving Environment (ORCE) was developed
to address these limitations (NICHD Early Child Care Research Network, 1996,
in press-a). Because psychological theory and research have indicated the
central role of experiences with caring adults for childrens well-being
and development, the ORCE focuses on this domain. Both time sampled behavioral
counts of caregiver actions (e.g., responds to vocalization, asks questions,
speaks negatively) and qualitative ratings of those behaviors over time to
characterize caregivers behavior with individual children are collected
during a minimum of four 44-minute observation cycles spread over a two-day
period. At the end of each 44-minute cycle, observers use 4-point ratings
scaled from 1 = not at all characteristic to 4 = highly
characteristic to describe caregiver behavior. A positive caregiving
composite score is created by obtaining a mean score across scales over all
of the ORCE cycles at a given age period. Higher scores indicate caregivers
who are more sensitive and responsive to a childs needs, who are warm
and positive, who are cognitively stimulating, and who are not detached or
hostile. Unlike the ECERS, ITERS, or FDCRS, the ORCE can be used in all types
of child care and with children across the first five years. Age-appropriate
behavioral descriptors for caregivers behaviors with infants, toddlers,
and preschoolers are provided.

Another commonly used process measure is the Caregiver Interaction Scale
(Arnett, 1989) that rates teachers sensitivity during interactions
with children. This 26-item measure yields three scores (sensitivitywarm,
attentive, engaged; harshnesscritical, punitive; detachmentlow
levels of interaction, interest, or supervision) which are combined to create
an overall caregiver quality score. The ratings are made after two 45-minute
observations conducted on two separate occasions by two separate observers.

The Assessment Profile (Abbott-Shim & Sibley, 1992a, 1992b) assesses
different aspects of quality, namely features related to health and safety,
physical facilities, and individualized child services. Different forms of
the instrument are available for child care homes and centers. These forms
list individual items that are viewed as exemplars of (a) healthy, safe settings,
(b) rich physical environments, and (c) settings that meet the needs of adult
staff. Individual items are scored using a yes/no format, with yes
designating items that were either observed or reported by staff. These items
can be scored reliably (see NICHD Early Child Care Research Network, 1996).
Caregivers have been observed to offer more positive caregiving in settings
that receive higher Profile scores (NICHD Early Child Care Research Network,
1996, in press-a).

The CC-HOME Inventory is a measure of process quality that uses a checklist
approach to create a quality score across multiple domains, including the
health and safety of the physical environment, variety of experiences, and
materials (NICHD Early Child Care Research Network, 1996). Derived from Bradley
and Caldwells well-known assessment of the quality of the home environment,
45 items are scored on a yes/no basis and then summed (alpha = .81). In one
study, children who attended better-quality child care homes as measured
by the CC-HOME Inventory obtained higher Bayley scores at 24 months and higher
school readiness and language comprehension scores at 36 months, in comparison
to children who attended poorer-quality child care homes (Clarke-Stewart,
Vandell, Burchinal, OBrien, and McCartney, 2000).

Other measures have been less successful in providing reliable and valid
assessments of process quality. For example, Lamb and colleagues failed to
find concurrent associations between child care quality and child functioning
in their study of child care in Sweden (Broberg, Hwang, Lamb, and Bookstein,
1990). One factor that likely contributed to the lack of significant relations
was problems with their quality measure. The Belsky-Walker Checklist (Broberg
et al., 1990) asks observers to check off if 13 positive events (e.g., caregiver
provided verbal elaboration, caregiver gives heightened emotional display;
signs of positive regard ) and 7 negative events (e.g., child cries; child
aimless; caregivers in non-child conversations) occur at least once during
3-minute observation intervals. This 3-minute time observation frame was
substantially longer than the 10- to 30-second intervals recommended for
recording social interactions (Yarrow and Zahn-Waxler, 1979). Consequently,
the checklist may have failed to detect meaningful distinctions in caregiver
behavior because the time interval was too long to detect meaningful differences.
This checklist underscores the challenge of designing and assessing process
quality. Detecting relations between process quality and child outcomes requires
robust measures.

Structural and Caregiver Characteristics

A second approach to describing child care quality is in terms of their
structural and caregiver characteristics. Characteristics such as child:adult
ratio, group class size, caregiver formal education, and caregiver specialized
training are viewed as more distal contributors to quality environments.
Structural and caregiver characteristics are the only quality indicators
obtained in survey studies such as the National Child Care Survey (Hofferth,
Brayfield, Deich, and Holcomb, 1991), the National Household Education Survey
(Hofferth et al., 1998), and the National Longitudinal Survey of Youth (Blau,
1999-c). Structural and caregiver characteristics have been collected in
addition to process-oriented measures in studies such as the Cost, Quality
and Outcome Study, thereby permitting relations between these characteristics
and process quality to be evaluated.

Relations between structural and caregiver characteristics and process quality
are well-documented in the research literature. Table
1 is a compilation of the studies conducted in the United States that
have considered this issue. The table includes information regarding sample
size, type of care setting, the structural and caregiver characteristics
that were measured, the process quality measures that were collected, and
findings that were obtained. As indicated in Table 1,
some studies have considered bivariate relations between structural and caregiver
characteristics, and process quality using Pearson correlations and t-tests.
Other studies (Blau, in press; NICHD Early Child Care Research Network, 1996,
in press-a; Phillipsen, Burchinal, Howes, and Cryer, 1997) utilized multiple
regression techniques in an effort to isolate the relative impact of different
characteristics. As documented on the table, the multivariate results are
consistent with the bivariate and global composite analyses. As is evident
in Table 1, studies have considered both global
composites of structural and caregiver characteristics and individual factors
in relation to process quality (Howes, 1990; Vandell and Powers, 1983).

When child:adult ratios are lower, caregivers spend less time managing children
in their classrooms and children appear less apathetic and distressed (Ruopp,
Travers, Glantz, and Coelen, 1979). When child:adult ratios are lower, caregivers
offer more stimulating, responsive, warm, and supportive care (Clarke-Stewart,
Gruber, and Fitzgerald, 1994; Howes, 1983; NICHD Early Child Care Research
Network, 1996, in press-a; Phillipsen et al., 1997; Volling and Feagans,
1995). Ratios also are associated with global process quality scores (Burchinal,
Roberts, Nabors, and Bryant, 1996; Howes, Phillips, and Whitebook, 1992;
McCartney, et al., 1997; Scarr, Eisenberg, and Deater-Deckard, 1994; Whitebook,
Howes, and Phillips, 1990). For example, in a study of 414 children who resided
in three states, Howes et al. (1992) determined that good and
very good scores on the ITERS and ECERS were more likely in infant
classrooms with ratios of 3:1 or less, in toddler classrooms with ratios
of 4:1 or less, and in preschool classrooms with ratios of 9:1 or less. More
than half of the infant classrooms with ratios higher than 4:1 and preschool
classrooms with ratios higher than 5:1 received scores that were categorized
as inadequate.

Group size also has been considered in relation to process quality. In
simultaneous multiple regressions that included group size, ratio, caregiver
education, and caregiver specialized training, the NICHD Study of Early Child
Care (1996; in press-a) determined group size to be uniquely associated with
positive caregiving. Similarly, Ruopp et al. (1979) reported group size to
predict caregiver behavior even when child:adult ratio was controlled. In
these studies, caregivers were more responsive, socially stimulating, and
less restrictive when there were fewer children in their classrooms. These
relations also are observed in child-care homes (Elicker, Fortner-Wood, and
Noppe, 1999; Stith and Davis, 1984).

Caregivers formal education and specialized training also are related
to quality of care. Caregivers who have more formal education (NICHD Early
Child Care Research Network, 1996; Phillipsen et al., 1997) and more specialized
training pertaining to children (Arnett, 1989; Berk, 1985; Howes, 1983, 1997)
offer care that is more stimulating, warm, and supportive. Highly educated
and specially trained caregivers also are more likely to organize materials
and activities into more age-appropriate environments for children (NICHD
Early Child Care Research Network, 1996). These settings are more likely
to receive higher scores on the global quality scales such as the ECERS,
ITERS, ORCE, and CC-HOME (Clarke-Stewart, et al., 2000; Howes and Smith,
1995; NICHD Early Child Care Research Network, 1996, in press-a).

Repeated-measure analyses conducted for children in the NICHD Study of Early
Child Care at 15, 24, and 36 months ascertained that group size and child:adult
ratios were stronger predictors of process quality for infants, whereas caregiver
educational background and training were stronger predictors of process quality
for preschoolers (NICHD Study of Early Child Care, in press-a). These relations
do not appear to be an artifact of restricted ranges. The standard deviations
for caregiver formal education and caregiving training were similar at different
assessment points. Standard deviations for ratio and group size increased
for older children. The differential patterns, then, suggest the merits of
an age-related strategy for improving process quality. Ratios and group size
may be more critical for infant care; caregiver training and education may
be more critical for preschoolers.

Caregiver wages is another factor associated with process quality (Howes,
Phillips, and Whitebook, 1992; Scarr et al., 1994). See
Table 1. In the Three-State Study, Scarr et al.
reported teacher wages to be the single best predictor of process quality.
In analyses of the Cost, Quality, and Outcome data set, Phillipsen et al.
(1997) determined lead teachers wages to significantly predict scores on
the ECERS and the Arnett sensitivity scales.

Although much of the research literature has reported significant relations
between structural and caregiver characteristics, and process quality, Blau
(in press) has cautioned that these associations may be the result of
uncontrolled factors that are confounded with the structural and caregiver
characteristics. He argues that these confounding factors might include center
policies, curriculum, and directors leadership skills. To address this
perceived shortcoming, Blau conducted secondary analyses on 274 child care
centers that were part of the Cost, Quality, and Outcomes Study. In his first
set of analyses, Blau conducted regressions to determine if individual structural
and caregiver characteristics were associated with process quality when other
factors (teacher, family, center characteristics) were controlled. His findings
were consistent with other reports. When child:adult ratios were larger,
ITERS and ECERS scores were lower. When caregivers had attended college or
training workshops and when caregivers had college degrees in fields related
to child care, ECERS scores were higher.

Blau then tested relations between structural-regulable characteristics and
process quality using a more stringent fixed-effects model that included
center as a control variable. This fixed-effects approach was possible because
two classrooms were typically observed in each center. In centers in which
there were both infants and preschoolers, one classroom of each type was
observed. In centers serving only preschoolers, two preschool classrooms
were selected randomly. When center was controlled along with type of classroom
(infant vs. preschool), relations between structural and caregiver features
and process quality were reduced. Blau interprets this reduction to mean
that unobserved center characteristics account for the previously reported
relations between structural factors and process quality. Our concern, however,
is that the center fixed-effect control is inappropriate. As Blau himself
noted, this approach requires within-center variability in the structural
characteristics. It is unlikely that classrooms in the same center are highly
variable in terms of caregiver training, ratio, or group size, especially
given that the model also controlled for type of classroom (infant/toddler
vs. preschool). The inclusion of the specific center as a control variable
resulted in an underestimation of effects.

Health and Safety Indicators of Quality

Global process quality measures such as the ECERS, CC-HOME, and Profile
Assessment include health and safety indicators as a component of process
quality. Research conducted in the medical and public health arenas has focused
more exclusively on these indicators in relation to childrens physical
health and safety. More hygienic practices by staff and children (Niffenegger,
1997; St. Sauver, Khurana, Kao, and Foxman, 1998) are associated with fewer
respiratory illnesses and other infectious diseases. These practices include
frequent handwashing after diapering, before meals, and after nose wiping.
Child injuries in child care settings are most likely to occur on playgrounds
and are most due to falls from climbing equipment (Briss, Sacks, Addis, Kresnow,
and ONeil, 1995; Browning, Runyon, and Kotch, 1996). Height of the
equipment and lack of an impact-absorbing surface under the equipment have
been consistently identified as the factors most highly associated with injuries
that required medical treatment. The North Carolina Smart Start initiative
was successful in improving the safety of child care centers with playground
improvement grants (Kotch and Guthrie, 1998).

Conclusions

The weight of the research evidence demonstrates significant relationships
between process quality, structural and caregiver characteristics, and health
and safety practices. The next section uses process, structural, and caregiver
measures to predict developmental outcomes for children.

There are substantial challenges for researchers and policy makers who seek
to answer questions about the effects of child care quality on childrens
development. One well-acknowledged difficulty is the absence of well-controlled
experiments in which children are randomly assigned to child care that varies
in quality. Instead, investigators have studied children whose families and
child care settings are willing to participate. This examination of naturally
occurring child care, as opposed to more controlled experiments, poses challenges
for researchers and policy makers (Blau, 1999c; Lamb, 1998; NICHD Early Child
Care Research Network, 1994; Vandell and Corasaniti, 1990). These challenges
are related to family/child selection biases and to restricted variability
in quality scores. Before reviewing research findings pertaining to effects
of quality, we briefly describe common strategies for addressing these research
challenges.

Methodological Challenges

Family/Child Selection Biases. The possibility that families differ
in their child care choices is a topic of interest in its own right (NICHD
Early Child Care Research Network, 1997; Singer, Fuller, Keiley, and Wolf,
1998). It also is a critical issue for investigators who are interested in
ascertaining the effects of child care on children (Howes and Olenick, 1986;
Vandell, 1997). The problem is that ostensible effects of child
care quality may be artifacts of family characteristics that are confounded
with child care quality. As a result of this concern, it has become standard
practice for researchers to incorporate family selection factors into their
analyses. As is evident in Tables 2 and
3, almost all studies conducted in recent years
have included controls for family characteristics.

As an example of this strategy, the NICHD Study of Early Child Care has utilized
three criteria for identifying family variables that are then used as selection
controls in analyses: (1) the family characteristic is significantly related
to child care, (2) the family characteristic is related to the child outcome
of interest, and (3) the family characteristic is not highly related to other
family factors. The third criterion is applied to reduce collinearity among
family characteristics.

At one level, concern about family selection bias is clearly merited. There
is evidence, for example, that type and quality of child care are related
to parents education and income (see Figure 1).

Parents who have higher incomes and more education are more likely to place
their children in centers that have higher ECERS scores, lower child:adult
ratios, and better-trained teachers (Blau, 1999c; Peisner-Feinberg and Burchinal,
1997). Children with more sensitive mothers are more likely to be placed
in care arrangements that offer more positive caregiving experiences (NICHD
Early Child Care Research Network, 1997). Children whose home environments
are more cognitively stimulating and more emotionally supportive are more
likely to be placed in child care settings that are stimulating and supportive
(NICHD Early Child Care Research Network, in press-b). These family factors,
if not controlled, may masquerade as child care effects.

At another level, however, selection effects do not appear to be as large
as initially thought. In the Cost, Quality, and Outcomes Study, for example,
the correlation between maternal education and the ECERS was .24; the correlation
between family income and the ECERS was .09. In the NICHD Study of Early
Child Care, correlations between maternal education and ORCE positive caregiving
ratings were .11 at 6 months, .14 at 15 months, .22 at 24 months, and .19
at 36 months. Correlations between family income and ORCE positive caregiving
were typically lower than these figures. These relatively modest associations
between child care quality and family factors suggest that selection effects
are not substantial, at least within the range of studies that have been
conducted. In the future, selection effects may be greater as welfare reform
is fully implemented and the numbers of children in child care increase.

Variability in Child Care Quality. The ability to detect child care
quality effects also is dependent on obtaining sufficient variability in
quality scores. Obviously, if there is no variation in quality, it is not
possible to detect variations associated with quality. If quality is sampled
within a truncated range, effects associated with quality are reduced and
larger samples are needed to detect differences. One reason that the Swedish
studies have not detected quality effects may be the restricted range of
the quality scores that were sampled, coupled with relatively small sample
sizes (Broberg, Wessels, Lamb, and Hwang, 1997; Lamb, Hwang, et al., 1988).
These same issues are pertinent to child care research in the United States,
when restricted ranges of quality are sampled and sample sizes are small.

Control for Prior Child Adjustment. A third challenge is determining
when and how to control appropriately for prior child adjustment in examinations
of child care effects. Some researchers have argued that stronger tests of
child care quality require controls for prior child adjustment. Such controls
could be used successfully in studies of after-school programs that controlled
for childrens adjustment prior to entry into the programs (Vandell
and Posner, 1999). Controls for prior child adjustment in studies of early
child care quality are more difficult. Children typically begin child care
during their first year of life, prior to the time that robust and reliable
measures of child cognitive, language, and social adjustment can be administered.
Using measures of child adjustment collected at some later period, after
substantial child care experience has accrued, does not make sense because
these measures may well be a reflection of the effects of quality to that
point. By controlling for child adjustment scores that were already affected
by quality, we may be eliminating (or at least minimizing) the very quality
effects that are of interest. This potential confounding of child care quality
and child adjustment scores means that fixed-effects models that control
for prior (or concurrent) child adjustment must be applied with caution.

The Conceptual Model

With these methodological challenges in mind, we turn to the conceptual framework
that guides our evaluation of child care quality. This model is presented
in Figure 2.

A central feature in the model is an awareness that children are not randomly
assigned to child care. Child care quality is expected to be related to family
characteristics including demographic, psychological, and attitudinal
differences. Because these family characteristicsincome, parental
education, maternal sensitivity, stimulating and supportive home
environmentsalso can predict childrens developmental outcomes,
it is necessary to control for them. Otherwise, quality effects may be
overestimated or underestimated. As shown in the model, research also needs
to take into account other child care parameters, such as amount of care
and type of care, that may be confounded with quality or that may contribute
independently to child outcomes.

Childrens developmental outcomes are considered in relation to process
quality and in relation to structural and caregiver characteristics.
Specifically, the model posits that process quality is directly related to
child developmental outcomes. Structural and caregiver characteristics are
posited to be indirectly related to child outcomes, through their influence
on process quality. It is expected that structural and caregiver characteristics
also directly influence child outcomes in ways that are not mediated through
the available measures of process quality. In the sections that follow, research
findings pertaining to this model are considered in terms of concurrent relations
between child care quality and childrens development, and in terms
of longer-term associations between child care quality and child adjustment.

Concurrent Associations between Process Quality and Child Outcomes

Table 2 is a summary description of results from
empirical studies that examined relations between process quality and child
developmental outcomes. The description includes sample size, childs
age at the time of the concurrent assessments, the measures of process quality
that were used, the measures of structural quality that were used, the controls
(if any) for family factors, the child developmental domains that were
considered, and a summary of findings.

As is evident is Table 2, some of the available
research focuses on relations between process quality measures and child
behavior in the child-care setting. Other research considers relations between
process quality and child behavior outside of child care. The former set
of studies provide descriptions of childrens immediate reactions to
caregiving experiences that are emotionally supportive and cognitively enriching
versus experiences that are less supportive and enriching. These studies
yield firsthand evidence about childrens reactions to care of varying
quality. The latter set of studies considers whether reactions to quality
experiences are evident in childrens behavior in other settings.

Process Quality and Childrens Behavior in Child Care. Several
investigators have delineated systematic relations between process quality
and childrens behavior in the child care setting (see
Table 2). For example, controlling for child gender
and family socioeconomic status, children appear happier in child care settings
where activities are developmentally appropriate and caregivers are more
involved (Hestenes, Kontos, and Bryan, 1993). Children show more intense
negative affect when their caregivers are less involved with them. Children
display closer and more secure attachment relationships with their caregivers
when the caregivers are more positive and responsive to the childrens
needs (Elicker et al., 1999; Howes et al., 1992; Howes and Smith, 1995).

Associations between caregiver-child interactions and childrens
interactions with peers also have been reported (see
Table 2). Children who have more positive
interactions with their caregivers and more secure relationships with their
caregivers appear more prosocial and positively engaged with their classmates
(Holloway and Reichart-Erickson, 1988; Howes et al., 1992; Kontos and
Wilcox-Herzog, 1997). Children who have opportunities to participate in
activities such as art, blocks, and dramatic play demonstrate greater cognitive
competence during their free play (Kontos and Wilcox-Herzog, 1997). Taken
together, these studies suggest that experiences associated with better quality
foster competent performance in the child care setting. By the same token,
children are less likely to display competent behavior in child care settings
characterized by lower process quality.

Process Quality and Childrens Behavior in Other Settings. The
next issue is whether process quality is related to childrens behavior
in other settings. Several studies (see
Table 2) have found higher quality child care
is associated with better performance on standardized language tests, even
when family characteristics are controlled (Burchinal et al., 1996; Dunn,
Beach, and Kontos, 1994; Goelman, 1988; McCartney, 1984; NICHD Early Child
Care Research Network, in press-b; Peisner-Feinberg and Burchinal, 1997;
Schliecker, White, and Jacobs, 1991). These relations are evident when the
process measure is a global score such as the ITERS, ECERS, or FDCRS, and
when the process measure focuses more narrowly on caregiver language stimulation.
It is notable that associations between process quality and language performance
are evident for child care that occurs in both centers and homes.

Childrens performance on standardized cognitive tests also has been
linked to concurrent process quality. Infants who attend centers with higher
ITERS scores receive better scores on the Bayley Mental Development Inventory
than infants in poorer quality centers (Burchinal et al., 1996). Similarly,
children who attend centers that have higher ECERS scores receive higher
scores on the CBI intelligence scale (Dunn, 1993). The Cost, Quality, and
Outcome Study reported that higher ECERS scores were associated with better
scores on the reading subtest of the Woodcock-Johnson (Peisner-Feinberg and
Burchinal, 1997).

Finally, process quality is related to childrens social and emotional
functioning. High-quality care as measured by the ECERS is related to greater
child interest and participation, whereas poorer process quality is associated
with heightened behavior problems (Hausfather, Tohari, LaRoche, and Engelsmann,
1997; Peisner-Feinberg and Burchinal, 1997). The Bermuda Study (Phillips,
McCartney, and Scarr, 1987) found higher ECERS scores to predict both caregiver
and parent reports of childrens considerateness and sociability, and
caregiver reports of childrens higher intelligence and task orientation
and less anxiety.

Although the majority of studies (see Table 2)
have reported significant relations between process measures of quality and
concurrent child functioning, it should be noted that there are exceptions.
Scarr and colleagues did not find relations between process quality and
childrens social outcomes (McCartney et al., 1997). Measurement problems
may have contributed to the lack of findings. For example, observers were
only moderately reliable on the measures of quality, with exact agreement
of 5558 percent between sites on the ITERS/ECERS. Cross-site reliability
in the classroom observations of childrens social behavior (a key dependent
variable) also was poor to moderate, with kappa coefficients ranging from
.40 to .76. The likelihood of detecting associations may have been hampered
by unreliable measurements.

Concurrent Associations between Structural and Caregiver Characteristics,
and Child Outcomes

There has been a longstanding interest in structural and caregiver
characteristics in relation to childrens developmental outcomes, in
part because the structural and caregiver characteristics are easier to measure
and to monitor than process quality. An early studythe National Day
Care Study (Ruopp et al., 1979)included a clinical trial in which 3-
and 4-year-olds were randomly assigned to 29 preschool classrooms with different
child:adult ratios and levels of staff education. Two levels of ratio (5.4:1
vs. 7.4:1) were contrasted along with three levels of staff education (B.A.,
Associate of Arts, or less than an A.A. in early childhood education). Child
behaviors were assessed at the beginning of the intervention and 9 months
later. Children assigned to classrooms with fewer children obtained greater
gains on measures of receptive language, general knowledge, cooperative behavior,
and verbal initiations, and exhibited less hostility and conflict in their
interactions with others than did children assigned to classrooms with larger
numbers of children. Children whose assigned teachers had more education
and training achieved greater gains in cooperative behavior, task persistence,
and school readiness than children whose teachers had less education and
training.

Correlational studies also have reported concurrent associations between
child:adult ratio and childrens language, cognitive, and social
functioning. Infants who attend centers with smaller child:adult ratios are
found to have better receptive and expressive language skills than children
who attend centers with larger child:adult ratios (Burchinal et al., 1996;
Vernon-Feagans, Emanuel, and Blood, 1997). Lower child:adult ratios also
are associated with higher Bayley scores (Burchinal et al., 1996) and with
better social knowledge and social behaviors (Holloway and Reichhart-Erickson,
1988).

Teachers education and training also are related concurrently to child
performance and adjustment. Burchinal et al. (1996) report that infants have
better expressive language skills when their caregivers are better educated.
Preschoolers receptive language skills are higher when caregivers have
at least an Associate of Arts degree in a child-related field (Howes, 1997).
Children whose caregivers have degrees in child-related fields received higher
CBI intelligence scores than children with less-educated caregivers (Dunn,
1993). Caregiver education and training in child care homes are similarly
related to childrens performance on standardized cognitive measures
(Clarke-Stewart et al., 2000).

Observations of childrens experiences in classrooms and child care
homes suggest why these relations might occur. Children are more likely to
engage in language activities, complex play with objects, and creative activities
in their classrooms when teachers have bachelor degrees in child-related
fields (Howes, 1997). Toddlers are more likely to talk with their caregivers
and to engage in complex play when classrooms have smaller child:adult ratios
(Howes and Rubenstein, 1985). Toddlers are more likely to cry and to have
their actions restricted in classrooms in which group sizes are larger (Howes
and Rubenstein, 1985). In child care homes, positive caregiving is more likely
when group sizes are smaller, caregivers are more educated, and caregivers
have more specialized training pertaining to children (Clarke-Stewart et
al., 2000).

An alternative research strategy has been to consider aggregated structural
and caregiver characteristics. For example, the NICHD Study of Early Child
Care (NICHD Early Child Care Research Network, 1999a) assessed four structural
and caregiver characteristics (child:staff ratio, group size, caregiver
specialized training in child development or early childhood education, and
caregiver formal education) in terms of guidelines recommended by the American
Public Health Association. The investigators then summed the number of structural
and caregiver characteristics that met recommended guidelines, resulting
in summed scores of 0 to 4. At 24 months, 1012 percent of classrooms
met all four standards, whereas 34 percent of the classrooms did so at 36
months. At 24 months, 9 percent of the observed centers met none of the
recommended standards; 3 percent of the centers met none of the standards
at 36 months.

Associations between the number of child care standards that were met and
child outcomes were then tested, with family income and maternal sensitivity
controlled (see Table 4). Children who
attended centers that met more recommended guidelines had fewer behavior
problems at 24 and 36 months, and higher school readiness and language
comprehension scores at 36 months. There were significant linear trends between
the number of recommended standards that were met and childrens concurrent
adjustment.

Analyses also compared children who were enrolled in classrooms that met
a given individual standard with children whose classrooms did not meet that
standard (see Table 4). At 24 months,
children displayed fewer behavior problems and more positive social behaviors
when centers met the recommended child:adult ratio. At 36 months, children
whose caregivers had specialized training or who had more formal education
exhibited fewer behavior problems and obtained higher school readiness and
language comprehension scores.

Investigators also have considered longer-term associations between process
quality and childrens developmental outcomes. A compilation of these
studies can be found in Table 3. Included in the
table are studies that considered relations between earlier child care
experiences and later adjustment. To our knowledge, there are no published
accounts that relate early child care quality to childrens adjustment
beyond middle childhood. Table 3 presents information
regarding sample size, controls for family factors, descriptions of the quality
measures, descriptions of the child outcomes, and specific findings.

Findings on this issue have been reported by the NICHD Study of Early Child
Care. Extensive information about the children, the families and child care
was collected during home visits (1, 6, 15, 24, and 36 months), child care
visits (6, 15, 24, and 36 months), and laboratory assessments (15, 24, and
36 months). Phone interviews were conducted every 3 months to track hours
and types of child care. Children who were in nonmaternal care for more than
10 hours a week were observed in that care. The investigators (NICHD Early
Child Care Research Network, 1998; 1999b; in press-b) asked if cumulative
positive caregiving (the average of ORCE positive caregiving ratings collected
during visits at each observation) is related to child developmental outcomes
at 24 and 36 months. Mental development at 24 months was assessed in the
laboratory with the Bayley. School readiness was measured using the Bracken
School Readiness Scale, a scale that assesses knowledge of color, letter
identification, number/counting, shapes, and comparisons. Expressive language
skills and receptive language skills were measured at 36 months using the
Reynell Developmental Language Scales. Mother and caregiver reports of child
behavior problems were obtained using composite scores from the Child Behavior
Checklist and the Adaptive Social Behavior Inventory. Peer skills were assessed
during a videotaped semistructured play situation with a friend.

Relations between cumulative positive caregiving and child development were
tested in analyses that controlled for child and family factors (child gender,
maternal education, family income, maternal psychological adjustment, home
quality assessed by Bradley and Caldwells HOME scale and videotaped
observations of mother-child interaction) and other aspects of child care
(time in center and total hours in care from 3 to 36 months).
Table 6 summarizes findings from regression
analyses and resultant partial rs that indicated effect sizes. As
shown, the quality of child care during the first 3 years was related to
childrens school readiness, expressive language, and receptive language
at 3 years. Also shown on Table 6 are comparisons
of children in high-quality and low-quality child care (defined with quartile
splits), using the same covariates. This extreme group approach yielded
d statistics. Effect sizes using this extreme group approach were
significant for measures of school readiness, expressive language, and receptive
language at 36 months.

In order to evaluate the magnitude of these findings, the NICHD investigators
conducted parallel analyses that tested relations between quality of the
home environment during the first 3 years and the child developmental outcomes
(using the same covariates), and relations between child care hours during
the first 3 years and child developmental outcomes (using the same covariates).
Table 6 presents these effect sizes as well.
Effects associated with quality of the home environment (the cumulative composite
scores created from the Bradley and Caldwell HOME scale and mother-child
interaction ratings) were roughly twice the size of the child care quality
score. Effects associated with child care hours were substantially smaller
than effects associated with child care quality. The NICHD investigators
argued that these findings suggest effects of child care quality assessed
longitudinally to age 3 years were neither huge nor trivial, but were large
enough to be meaningful. It also should be noted that these effect sizes
are likely to be a conservative estimate because of the selective participation
by higher-quality settings. If the poorest quality child care settings refused
to allow observations to be conducted, the range of quality scores would
be truncated, resulting in smaller effect sizes.

Longer-term findings obtained from the Otitis Media Study (Burchinal, Roberts,
Riggins, Zeisel, Neebe, and Bryant, in press) are consistent with those reported
in the NICHD study. In that study, hierarchical linear models were tested.
Observations of classroom quality obtained annually over a 3-year period
were used to predict childrens adjustment up to age 3 years. Higher-quality
child care over time was associated with better cognitive development, better
receptive and expressive language skills, and better functional communication
skills over time, controlling for child gender, family poverty status, and
home environment quality.

A limitation with both of these reports is that children were studied only
to age 3. Thus, it cannot be ascertained if early effects are harbingers
of later differences or if these effects dissipate by the time that children
enter grade school. As additional findings from these ongoing investigations
become available, they can be used to identify conditions under which early
child care quality differences are maintained or dissipate.

In the meantime, the Cost, Quality, and Outcomes Study has information that
is relevant to this issue (Peisner-Feinberg et al., 1999). Started in 1993,
observations were conducted in child care centers located in four
statesCalifornia, Colorado, Connecticut, and North Carolinathat
varied in licensing standards. Centers were evenly distributed in each state
into nonprofit and for-profit programs. Within the eligible programs, 509
preschool classrooms and 224 infant/toddler classrooms were studied. Process
quality was rated using the ECERS or ITERS, the Caregiver Interaction Scale
(Arnett, 1989), and the Teacher Involvement Scale (Howes and Stewart, 1987).
Quality indicators were combined into a single process quality composite.

A subsample of children was followed through 2 years of child care and the
first 3 years of formal schooling (kindergarten through second grade). Children
were assessed for receptive language skills, reading ability, and math skills.
Child care and school teachers rated the childrens cognitive/attention
skills, sociability, and problem behaviors each year. Longitudinal hierarchical
linear models examined relations between the child care quality composite
collected at age 4 (Time 1) and childrens developmental outcomes through
grade 2. In all analyses, selection factors (maternal education, childs
gender and ethnicity) were controlled statistically.

Children who were enrolled in higher-quality child care classrooms as
preschoolers were found to have better receptive language skills. Effect
sizes for receptive language were moderate for the preschool period (.60
and .51 for the 2 years preceding school entry), more modest in kindergarten
(.30), and not significant in second grade. Child care quality also was related
to childrens math skills. Children who were enrolled in higher-quality
child care had better math skills prior to school entry and during kindergarten
and second grade, with modest effect sizes across the years (.20.29).
The relation was stronger for children whose mothers had less education.
In further analyses that controlled for the quality of the elementary school
classroom, the relations between child care quality and childrens math
skills were maintained. It is notable that a similar finding was obtained
in research conducted in Sweden. Broberg et al. (1997) found that process
quality assessed using the Belsky and Walker checklist at 16, 28, and 40
months predicted better math skills at age 8, even after controlling for
child and family factors.

Other research has considered longer-term associations between child care
quality and childrens social-emotional outcomes. Howes (1990) focused
on one particular aspect of process quality, child care socialization practices,
in relation to childrens subsequent developmental outcomes.
Caregivers involvement and investment in child compliance were measured
during naturalistic observations in the child care setting. Having a more
involved and invested caregiver during the first 3 years was associated with
kindergarten teachers reports that the children had fewer behavior
problems and better verbal IQs.

Alternative Views. As shown in Table 3, some
investigators have not found relations between child care quality and later
developmental outcomes. For example, Chin-Quee and Scarr (1994) did not find
evidence of long-term effects in a longitudinal follow-up of the Bermuda
study. In the initial study, concurrent associations were reported between
process quality as measured by the ECERS and child developmental outcomes
(McCartney, 1984; Phillips et al., 1987). In the follow-up study, teachers
rated social competence (peer relations and cooperative behavior) and academic
achievement for 97 of the original sample of 166, when children were in grades
1 and 2 (Time 2) and grades 3 and 4 (Time 3). Associations between the quality
indicators during the preschool years and competence at school were tested
with hierarchical regressions in which parental values, age of entry into
care, and total amount of child care before school entry were controlled.
Neither the global quality score nor the specific measures of caregiver language
predicted childrens social competence and academic achievement at Time
2 or Time 3.

A longitudinal follow-up of children who participated in the Three-State
Study also failed to detect long-term effects (Deater-Deckard, Pinkerton,
and Scarr, 1996). In this project, assessments of child care quality were
first obtained in 363 classrooms located in 120 centers in three states (Georgia,
Virginia, Massachusetts) when 718 study children were infants, toddlers,
and preschoolers. Process quality ratings were obtained by pulling items
pertaining to teacher-child interaction from the ECERS and ITERS and the
Assessment Profile (a process measure scored for presence or absence of specific
items). Four years later, follow-up assessments were conducted for 141 of
the original sample. Multiple regressions controlled for child (child adjustment
at Time 1, age at Time 2, child gender) and family characteristics (SES,
a composite of parenting stress and low emotional support, maternal endorsement
of harsh discipline practices). The child care quality measure was a composite
of the ITERS/ECERS, the Assessment Profile that measures physical facilities,
caregiver training and education, and caregiver wages. In these analyses,
the child care quality composite score at Time 1 did not predict changes
in childrens behavior problems or social withdrawal at Time 2.

Although Scarr (1998) has argued that these studies demonstrate that child
care quality has little or no long-term impact on childrens development,
the findings must be interpreted with caution. Both studies are based on
the assumption that a quality assessment obtained at one point in time is
an adequate and accurate representation of child care quality. Single assessments
might be sufficient if care arrangements and quality are stable; however,
a single observation is not adequate if care is unstable or changing. In
the Bermuda sample, Chin-Quee and Scarr (1994) reported that half the children
experienced one, two, or three arrangements during the intervening period,
and half experienced more than three arrangement changes. In the Three-State
study, no information about child care quality in the intervening four years
was collected. In both studies, it is difficult to interpret the meaning
of the null findings in light of no information about child care quality
across early childhood. Stronger, more valid tests of the effects of child
care quality need to take into account cumulative quality and the pattern
of quality over time.

The lack of long-term relations in the Three State Study may also reflect
limitations in the assessment of process quality. Only moderate interobserver
agreement was reported across the three research sites.58 for the ECERS
and .55 for the ITERS (McCartney et al., 1997). Lower relations between process
quality and child outcomes would be expected when process quality scores
are less reliable.

Longer-Term Associations between Structural and Caregiver Characteristics
and Child Outcomes

Other studies have considered relations between structural and caregiver
characteristics in relation to childrens subsequent developmental outcomes
(see Table 3). Howes (1988), for example, examined
structural and caregiver characteristics at 3 years in relation to
childrens first-grade adjustment. Quality in 81 centers was defined
in terms of five areas: teacher training, child:adult ratio, group size,
a planned curriculum, and space. Higher-quality care met recognized standards
in all five areas; medium-quality care met standards on three or four dimensions,
and low-quality care met three or fewer standards. During the intervening
period, the 87 children attended the same university lab school, meaning
that they experienced classes with the same or similar structural and caregiver
characteristics.

In analyses that controlled for maternal work status, family structure, and
maternal education, Howes found that children who had attended higher-quality
child care programs prior to enrollment in the university school had fewer
behavior problems and better work habits as compared to children who had
attended lower quality programs. Additionally, boys who had attended
higher-quality centers received better first-grade teacher ratings of academic
performance compared to other boys.

Using a different sample of 80 children who were enrolled in center-based
care, Howes (1990) examined relations between a structural quality composite
(child:adult ratio, caregiver training, caregiver stability) measured at
18, 24, 30, and 36 months, and childrens kindergarten adjustment.
High-quality care was defined as ratios of 4:1 or less for children who were
< 2 years and 7:1 for children > 2 years, caregivers with 12
units of college-level child development courses, and no more than two different
primary caregivers in the prior year. Low-quality care was defined as ratios
of 6:1 or higher for children who were 2 years or less and ratios of 10:1
for children who were older than 2 years, caregivers with no formal child
development training, and more than two primary caregivers in the prior year.

Associations between structural quality in the first 3 years and childrens
later preschool and kindergarten adjustment were tested, controlling for
a family socialization composite and a family demographic composite. Children
with a history of poor-quality child care during the first 3 years were rated
by their preschool teachers as being more difficult and by their kindergarten
teachers as being more hostile. The children also engaged in less social
pretend play and displayed less positive affect in their preschool classroom.

Recent research from the Otitis Media Study has focused on specific structural
and caregiver characteristics in relation to subsequent child developmental
outcomes (Burchinal et al., in press). The researchers initially recruited
89 children who were 4 to 9 months of age for a study of the effects of otitis
media on childrens development. Children attended 27 centers that varied
in quality. Child care quality was assessed annually using the ECERS and
ITERS. Children whose child care classrooms met recommended guidelines for
child-staff ratios exhibited better receptive language and functional
communication skills over time as compared to children whose classrooms did
not meet recommended ratio guidelines, controlling for child gender, family
poverty, and cognitive stimulation and emotional support in the home. Caregiver
education also predicted childrens adjustment, but only for girls:
Girls whose caregivers had at least 14 years of education (with or without
early childhood training) had better cognitive and receptive language skills
over time compared to girls whose caregivers had fewer than 14 years of
education, controlling for the family factors.

Blau (1999c) also has examined structural and caregiver characteristics in
relation to childrens subsequent developmental outcomes. For these
analyses, he used secondary data obtained from the National Longitudinal
Survey of Youth (NLSY), an ongoing nationally representative study of 12,652
youth begun in 1979. Beginning in 1986, information about children of the
female respondents was collected. Mothers also provided information about
their childrens primary child care arrangementsthe number of
children cared for in the group, the number of adult care providers in the
arrangement, and whether the main caregiver had specialized training in early
childhood education or child development. Blau then averaged these maternal
reports of structural and caregiver characteristics through age 2 and for
ages 35 years. Children completed the Peabody Picture Vocabulary Test
(PPVT), a measure of receptive language skills, at 3 years or older. Mothers
reported on childrens behavior problems at 4 years or older. Children
completed math and reading subscales of the Peabody Individual Achievement
Test (PIAT) at 5 years or older.

Simple correlations revealed statistically significant, but small, associations
between mothers reports of caregiver training when the children were
in infant/toddler care and the childrens later performance. Children
whose mothers reported that their caregivers had more specialized training
obtained higher math and receptive language scores. When type of care was
controlled, these associations continued to be significant. Blau then asked
if these structural and caregiver factors uniquely predicted child performance
in a regression model that included 64 additional child care and family
variables. These controls included number of arrangements that were used,
hours per week in care, months per year in care, paid cash for care, cost
of care, center care, family day care home, relative care, child gender,
cognitive stimulation, emotional support, Hispanic ethnicity, black ethnicity,
grandmother worked when mother was 14, mothers education,
grandmothers education, fraction of mothers preschool years her
mother was present, fraction of mothers high school years her father
was present, month of pregnancy in which mother first received prenatal care,
childs birth order, Catholic, child received well-care visit in first
quarter, mothers age, mothers age at birth of child, siblings
in various age groups, and fraction of pregnancy during which mother worked.
In ordinary least squares regression analyses, relations between maternal
reports of caregiver training and childrens math and receptive language
scores were no longer evident when these other variables were controlled.
From these analyses, Blau concluded:

There seems to be little association on average between child care
inputs experienced during the first three years of life and subsequent child
development, controlling for family background and the home environment.
(p. 20)

Blaus conclusion does not appear warranted, for several reasons. First,
his analyses relied on maternal reports of structural and caregiver
characteristics. Questions can be raised about whether mothers can provide
this information accurately, especially retrospectively. Unfortunately, Blau
provides no evidence regarding the accuracy of these reports. In order to
estimate the accuracy of mothers concurrent reports of structural and
caregiver characteristics, we turned to the NICHD Study of Early Child Care
data set, which included both mothers and caregivers reports
of group size and child-adult ratio. These reports were compared to
observers independent counts of ratio and group size during 2-day visits.
The mean correlation between mothers and caregivers reports of
group size for children in centers was .55 (range = .51 to .63). The mean
correlation between maternal reports of child:adult ratio and observed ratios
was .33 (range = .27 to .42). These figures suggest that mother concurrent
reports can be viewed as moderately reliable. Maternal retrospective reports
of group size and ratio appear to be considerably less reliable. In other
studies, near-zero correlations were obtained between observational assessments
of group size and child-adult ratio when children were age 4 years (Vandell
and Powers, 1983) and maternal retrospective reports of these same structural
variables 4 years later (Vandell, Henderson, and Wilson, 1988).

To our knowledge, there are no data available from which the accuracy of
maternal reports of caregiver training can be evaluated. We suspect, based
on our own personal experiences, that mothers are less likely to know about
caregiver training than about group size and ratio, which they can observe.
Taken together, we believe that the lack of precision in the mothers
reports in the NLSY result in an underestimation of effects associated with
structural and caregiver characteristics.

Blau also adopted a stringent, perhaps unrealistic, test for long-term effects.
Child outcomes were assessed a minimum of 2 years after mothers reported
structural and caregiver characteristics, and the lag appears to have averaged
5 years or more because children were reported to be, on average, 8 years
of age when outcomes were assessed. Interestingly, there was some evidence
of longitudinal associations when shorter time lags were considered (even
though mothers reports were used). For example, significant relations
were found between maternal reports of child:adult ratios and caregiver training
during the first 3 years and behavioral adjustment and math scores for children
who were less than 9 years of age. Relations were not evident for very long
time period, i.e., children who were older than 9 years. Smaller group sizes
during the preschool period (35 years) were associated with higher
scores on math, reading, and language performance. Lower child:staff ratios
were associated with fewer behavior problems. The long lag between the infant
quality reports and the child outcome assessments is further complicated
by the omission of quality reports during the older preschool years, resulting
in an underestimation of effects associated with child care quality.

Conclusions. Structural and caregiver characteristics have been found
to be associated with childrens academic, cognitive, behavioral, and
social development. Smaller group sizes, lower child-caregiver ratios, and
more caregiver training and education appear to have positive effects on
these important developmental outcomes. Future work might address threshold
levels for these child care characteristics, or the point at which further
improvements in structural quality do not yield additional developmental
benefits for children.

An Economists Interpretation of the Link between Child Care Quality
and Child Outcomes

The traditional approach of those working in the field of developmental
psychology is to use standardized regression coefficients in hierarchical
regression models. These seem quite different from the methods employed by
economists, but the full model used is a standard OLS regression model, and
the standardized coefficients can be converted into the nonnormalized
coefficients more traditional in the economics discipline. Doing so allows
us to address the question of the expected change in developmental outcomes
of children were quality to be improved based upon standard OLS estimates
(see Hanushek and Jackson, 1977).

Using estimates based on NICHD data, we perceive that the quality of child
care can indeed make a difference. Table 7
reports on the cognitive and language results for the NICHD samples at ages
15 months, 24 months and 36 months (NICHD Early Child Care Research Network,
in press-b). Three outcome measures are used: for the younger two ages, the
Bayley, CDI vocabulary production, and CDI vocabulary comprehension tests
are used; for the oldest age group (36 months) the Bracken school readiness,
Reynell expressive language and Reynell verbal comprehension tests are used.
(See above for a more detailed discussion of these tests.) In addition to
the measures of child care quality, the model includes measures of parental
background, quality of the home, the child care setting, and time spent in
child care. These are an attempt to minimize the role of parental selection
of child care in order to capture the effects of child care quality differences
on measures of child development.

Two models are presented for each age group and outcome measure. The first
tests for the effects of the child care quality using a cumulative score
of positive caregiving rating, while the second adds a specific measure of
language stimulation. Caregivers behaviors were assessed during four
44-minute observations over two half-days at 6, 15, 24, and 36 months. These
were combined into the cumulative positive caregiving rating.

We converted the standardized coefficients reported in NICHD (in press-b),
into nonstandardized coefficients. Table 7
only reports those for child care quality that are statistically significant
at the 5 percent level. Combining these with the measures of quality and
reinterpreting the standardized coefficients indicates the following effects.

The expected improvement in the CDI vocabulary production test for toddlers
aged 15 months, when their care quality shifts from one standard deviation
below the mean to one standard deviation above, is nearly 7 points, or 24
percent; if the shift is from the minimum score (5) to the maximum (20) in
caregiver rating, the estimated gain is 18 points. (Note that the standard
deviation is 2.9, within a range of 520.) For the vocabulary comprehension
score, shifting from one standard deviation below the mean leads to an expected
increase of 8 points; and moving a child from the minimum score to the maximum
score in caregiver rating is expected to increase a childs score by
21.6 points, or 55 percent of the mean.

At age 24 months, statistically significant changes are registered for the
Bayley test and the sentence comprehension test. The Bayley estimates produce
an expected increase of about 5 points when the shift is from one standard
deviation below the mean to one above. The sentence comprehension results
produce an expected increase of 7 points. A shift from the lowest caregiver
to the highest increases expected performance on the vocabulary test by about
40 percent relative to the mean, but only about 13 percent in the case of
the Bayley test. (Note that for the 24 month olds the standard deviation
is 2.9 as well, and the range is the same as that for those 15 months old,
520.) The expected changes are larger for those aged 36 months than
for those aged 24 months.

For the Bracken school readiness test at age 36 months, a shift from one
standard deviation below the mean on the caregiving rating to one above is
expected to lead to an increase of 6.9 points. (Note that the caregiver rating
has a larger range for those aged 36 months, 728, while the standard
deviation is 3.3.) The same shift in caregiver quality is expected to lead
to a 5-point increase in the expressive language score and an 8.6 point increase
in the verbal comprehension score, relative to the mean. A shift from the
lowest rating to the highest for caregiver rating is expected to result in
a shift of about 50 percent relative to the mean for each of these three
outcomes. These estimates give us some sense of the magnitude of the possible
changes in childrens outcomes as a result of improvements in positive
caregiver rating.

We can do a similar exercise with the second measure of quality, language
stimulation. This measure is added to the regression in an alternative
specification. In most cases the addition of this measure reduces the estimated
impact of positive caregiving. (Because language stimulation is a major component
of caregiving quality, this is not surprising.) We simulate the impact of
language stimulation only for ages 15 months and 24 months, where it is
statistically significant for all three of the child development outcome
measures.

For children 15 and 24 months of age, having a child care arrangement in
which more language stimulation is provided can play a small but significant
role in improving all three of the outcome measures. For children of 15 months,
simulating an improvement in caregiver language stimulation from one standard
deviation below the mean to one above increases performance on the Bayley
test by nearly four points, by 12 points on the CDI vocabulary production
test and by about 9 points on the CDI sentence comprehension test. At 24
months of age, a child exposed to a level of language stimulation one standard
deviation below the average is expected to gain about 5 points on the Bayley
test, or about 4 percent relative to the mean, were the child moved to an
arrangement with a rating one standard deviation above the norm, or by 61
units (about one third of the full range of 0180). The same child would
be expected to gain 12 points on the CDI sentence comprehension test, or
nearly 30 percent relative to the mean. And the same child would be expected
to gain about 9 points on the CDI vocabulary production test, or about 20
percent relative to the mean.

The NICHD group also estimated models with both concurrent and lagged quality
measures (NICHD, in press-b). Their results suggest that the cumulative impact
of child care quality may be far greater than the concurrent impact. In
Table 8 we provide two examples, one for
children at 24 months of age using caregiver quality measures at 15 and
1524 months, and one at 36 months of age using quality measures from
1524 months and 36 months. Only those quality measures which are
statistically significant at the 5 percent level are reported. Similar measures
for language stimulation are chosen as the cognitive outcome measure. Both
sets of results suggest that there is a lagged effect of language stimulation
and that the cumulative effect of exposure to higher levels of language
stimulation appears to be greater than the concurrent impact alone. In the
case of those aged 24 months, the converted results suggest that a child
who was in a child care arrangement over this entire period that was one
standard deviation below the mean (calculated at both 15 and 24 months) is
simulated to gain about 30 points on a CDI vocabulary production test if
moved to one above the mean. Looking at only the concurrent language stimulation,
an increase of 11 points, or about one-third of the full cumulative gain,
is simulated. In the case of 36 those aged months, we find that both language
stimulation and overall caregiver quality are significantly associated with
performance on the Reynell vocabulary comprehension test measured at 36 months,
and that only the lagged measure of language stimulation is statistically
significant among the two lagged measures of quality. Among these 36-month-olds,
we simulate a combined gain of 11 points on the Reynell vocabulary test if
the child moved from one standard deviation below the mean on both quality
measures to one above the mean over the entire period from 15 months to 36
months. This far exceeds the simulated increase if only the contemporary
measures were modified. The respective means of the outcome measures are
shown on the table.

The magnitudes of simulated change are large, but the resulting changes are
also rather large, suggesting that caregiver quality can significantly influence
these outcomes. All of these estimates are subject to the usual caveat that
the underlying estimates may not be causal. We should also note that the
measures of quality are based on limited observation, so that the effect
captured is likely to underestimate the true effect of quality.

Other Outcomes

We now briefly review the findings from a small set of early childhood
intervention studies that look at such long-term outcomes as criminal activity,
earnings, and the use of cash welfare assistance. The Syracuse Family Development
Research Program was a small program that enrolled slightly more than 200
children and followed them for 5 years. It was one of the earlier programs,
beginning in 1969. The intervention included infant and preschool enrollment
in Syracuse Universitys preschool program as well as direct provision
of information on raising children, nutrition, etc. to the parents. The follow-up
analysis found that by age 15, 6 percent of the experimental group had been
referred to probation as compared to 22 percent of the controls. Through
based on very small numbers, the very large differences provide some evidence
that the combined interventions had a positive effect on the reduction of
crime (Lally, Mangione and Honig, 1988).

Perhaps the best-known early intervention project is the Carolina Abecedarian
Project (Campbell and Ramey, 1995; Ramey, Campbell, and Blair, 1998; Ramey
et al., in press). This clinical trial began at 6 weeks postpartum and included
(1) a randomized control group (n = 23) that received family support social
services, pediatric care, and child nutritional supplements, (2) an experimental
group (n = 25) that received the services of a high-quality center-based
intervention for the first 5 years and additional educational support services
from kindergarten to grade two, (3) an experimental group (n = 24) that received
only the early intervention, and (4) an experimental group (n = 24) that
received only the K-2 educational support. IQ scores at 8 years and 12 years
were significantly higher for preschool participants than for other children.
Furthermore, children who had participated in the preschool program had higher
scores on tests of reading and mathematics achievement at 8 and 12 years.
They were less likely to be retained a grade at ages 8, 12, and 15, and they
were also less likely to be placed in special education. The most recent
follow-up report from this research team (Early Learning, Later Success:
the Abecedarian Study, 1999) included findings to 21 years. Intervention
children were reported to be older, on average, when their first child was
born and to have been more likely to attend a four-year college.

The Perry Preschool Project (Schweinhart, Barnes, Weikart, et al., 1993)
involving 123 black children has reported long-term follow-up to 27 years.
The experimental group consisted of 45 children who entered the preschool
program at age 3 and an additional 13 who entered at age 4, attending a half-day
center-based program and receiving teacher home visits. The researchers report
that the experimental group had a somewhat lower probability of ever being
arrested by age 27 (57 versus 69 percent), but a larger difference in the
average number of lifetime arrests by age 27 (2.3 versus 4.6). Differences
in the proportion receiving public assistance by age 27 were also large:
15 compared to 32 percent. Mean earnings were far higher for the experimental
group than the control group at age 27: monthly reported mean earnings were
$1,219 for experimentals, $766 for controls.

Participation in the Chicago Child-Parent Centers (CPC) also has been related
to long-term beneficial effects (Reynolds et al., 2000). This project has
followed the educational and social development of 1,539 African-American
(93 percent) and Hispanic (7 percent) children as they grew up in high-poverty
neighborhoods in central city Chicago. Some of the children (n = 989)
participated in government-funded (Title I) early childhood programs in
1985-1986, whereas others did not (n = 550). A rich array of data, including
surveys from teachers, parents, school administrative records, standardized
tests, and the children themselves have been collected since that time. Children
who participated in the CPC preschool programs obtained significantly higher
math and reading achievement test scores at 5, 8, and 14 years, even after
controlling for family risk status, child gender, and later program
participation. At age 20, participants in the CPC were more likely to have
completed high school and to have low rates of juvenile crime.

Even though only a few studies have followed children into adulthood, it
is notable that all find some evidence of long-term gains.

In much of the existing literature linking parental employment and child
care, the primary issue is the affordability of care and the elasticity of
response to child care costs. In this sense one can see the potential for
a trade-off between quality of care and labor force participation, in that
higher-quality care is likely to be more costly. A parent facing that higher
cost may decide to forgo or limit employment or to elect lower-quality and
less costly care (Scarr, 1998). Maume (1991) found that a $10 increase in
the weekly cost of child care was associated with a 1.6 percent increase
in the probability of exiting employment within a year. A slightly earlier
study by Blau and Philip (1989) also provided evidence that an increase in
the cost of care was associated with an increased probability of a mother
leaving the labor force.

Quality of care may influence employment in several ways: parents may be
reluctant to leave their child in a low-quality, unsafe environment or with
adults who do not provide a stimulating or warm environment for their child.
This may be a particular problem for lower-income families, who have more
limited choices of providers. In contrast, a safe, warm, stimulating environment
may encourage employment and longer hours of work. Parents may also be more
effective employees if they do not have concerns about the environment in
which their children spend a good part of each working day. Having well-cared-for
children may also lead to employees with higher productivity than those whose
children are left in less satisfactory environments. Parents may also be
more likely to be on time to work and less likely to miss time from work
if their children are cared for in a safe, warm and stimulating environment.

Evidence. There is limited evidence on whether higher-quality care
has positive impacts on parental employment, because there have been few
studies. The available evidence suggests that among low-income women,
higher-quality child care may increase employment, stability of employment,
and hours of work. See Table 8 for detail
on these studies.

Meyers (1993) has explored how a mothers perception of the quality
of her childs care and the convenience of the child care arrangement
affected her labor market progress in the JOBS program. The results show
that a mothers perception of the safety of her childs care
arrangement and the trustworthiness of the provider were significant predictors
of the mothers continued participation in the JOBS program and in labor
force participation more generally. Mothers also responded to the ratio of
children to staff: those mothers who reported that the ratio of the children
to adults in their care arrangement exceeded professionally recommended standards
were more than twice as likely to drop out of the program than mothers who
reported that their childs care arrangement met the standard.

Additional evidence that quality plays a role in womens labor force
participation comes from another experiment: the Teenage Parent Demonstration.
As reported in Ross and Paulsell (1998), among the group of first-time teenage
welfare recipients whose members were randomly assigned to the program, which
required employment, job training or schooling, nearly a third reported that
the quality of child care was a problem that led them to stop working or
to change hours and/or activities. Ross and Paulsell interpret this to mean
that Mothers who are required to work as a condition of receiving welfare
benefits may try to manage with lower-quality child care than they would
in the absence of such a requirement, but this low-quality care may be the
reasons that mothers interrupt their employment activities. (p. 40)

Brooks-Gunn et al. (1994) evaluated an early intervention program, the Infant
Health and Development Program, in terms of its impact on mothers
employment. This experiment focused on low-birthweight infants and used random
assignment to an intervention program that provided center-based child care
when the child was 2 to 3 years of age. The authors report that mothers in
the intervention group were significantly more likely to be working than
women in the control group. Effects were particularly pronounced for mothers
with a high school degree or less schooling. Similar beneficial effects of
high- quality child care on mothers subsequent educational achievement
were evident in the high-risk sample that participated in the Abecedarian
clinical trials (Ramey et al., in press). Benasich, Brooks-Gunn, and Clewell
(1992) report qualitatively similar results for several other early intervention
programs (pp. 4142).

Other evidence (see Hofferth, 1999) that child care quality can influence
labor market participation can be found in research studies that differentiate
formal arrangements from informal arrangements. These analyses show that
parents miss work more often and are late more often if they use informal
arrangements. The big difference seems to be the stability of the
arrangementan element of quality.

The evidence reviewed above indicates that child care quality has meaningful
effects on children and their parents. Our next question considers the quality
of the care that is available in the United States. One part of this question
is a determination of whether high-quality care (of the sort that fosters
positive developmental outcomes) is the norm or the exception. The flip side
of this question is a determination of the likelihood that children are in
poor-quality care that can impair development. Unfortunately, at the current
time it is not possible to provide a definitive response to these questions,
because observations of process quality have not been conducted for a nationally
representative sample of children. In the absence of such a report, we must
reply on existing data from multisite studies that provide suggestions about
the distribution of quality of care in the United States.

The Cost, Quality, and Outcomes Study (Helburn et al., 1995) provides a
perspective on center-based care. ECERS assessments were conducted in 398
centers located in four states that varied in economic health and child care
regulations. In that study, 12 percent of the centers received ECERS scores
lower than 3, indicating care that was less than minimal quality, and 15
percent received ECERS scores higher than 5, indicating good-quality care.
The remainder of the centers were evenly divided between those receiving
scores in the 3s (37 percent) and scores in the 4s (37 percent). This
distribution of quality scores in the observed settings, however, may be
an optimistic view. The observed centers represented only 52 percent of the
eligible centers; the remainder declined to participate. It seems likely
that the nonobserved settings offered care that was lower in quality.

The Relative and Family Day Care Study (Kontos, Howes, Shinn, and Galinsky,
1995) provides a perspective on quality of care in homes. FDCRS scores were
obtained in 226 child care homes and relative care settings in three communities.
Minority race, low-income, and nonregulated home settings were over sampled
so that the investigators could study the effects of these factors on observed
quality. In that study, 34 percent of the child care homes received FDCRS
scores of less than 3 and were described as inadequate, 58 percent
were adequate/custodial, and 8 percent were good.
These unadjusted quality estimates are probably negatively biased, because
two of the three states (Texas and North Carolina) have less stringent
regulations for child care homes than other states and because nonregulated
and low-income settings were over sampled.

Perhaps the best available estimate of process quality for children 3 years
or younger is provided by the NICHD Study of Early Child Care. Observations
were conducted in nine states (Arkansas, California, Kansas, Massachusetts,
North Carolina, Pennsylvania, Virginia, Washington, Wisconsin) and included
urban, suburban, and rural communities. The distribution of child care
regulations in those states paralleled those in the United States. Observations
were conducted in all types of nonmaternal care settings, including grandparents,
in-home caregivers, child care homes, and centers. A total of 612 child care
settings were assessed at 15 months, 630 child care settings at 24 months,
and 674 child care settings at 36 months.

The study sample of 1,364 families was drawn from hospitals at the 10 research
sites and included ethnic minorities (24 percent), mothers without a high
school education (10 percent), and single-parent households (14 percent)
as well as white, middle-class and two-parent households. At 15 months, 17
percent of the households had incomes below established poverty levels
(income-to-needs ratio < 1.0). An additional 18 percent of the sample
had incomes near poverty (income to needs ratio 1.0 1.99) (NICHD Early
Child Care Research Network, 1997). The sampling plan yielded a large and
diverse sample, but it is not nationally representative. The sampling plan
also did not include adolescent mothers (3.8 percent of the potential families
in the hospitals), mothers who did not speak English (4.4 percent), and infants
of multiple births, with obvious disabilities, or extended hospital stays
postpartum (7.7 percent of the births).

Results from the NICHD Study of Early Child Care observations (NICHD Early
Child Care Research Network, in press-a) are summarized in
Table 9. ORCE ratings less than 2 indicate
poor-quality care. Scores of 2 to less than 3 indicate fair-quality care.
Scores equal to 3 but less than 3.5 indicate good-quality care, and scores
of 3.5 or higher indicate excellent-quality care. Care was most often judged
to be only fair in quality. Relatively little care was observed at the extremes,
with 6 percent of the settings offering poor quality care and 11 percent
of the settings offering excellent care. Poor-quality care was more likely
in centers serving infants and toddlers than in centers serving older children
(10 percent versus 4 percent).

An extrapolation to the quality of care in the United States was derived
by applying NICHD observational parameters, stratified by maternal education,
child age, and care type to the distribution of American families documented
in the National Household Education Survey
(1998).(2) This stratification was needed
because the NICHD investigators determined that variations in process quality
were associated with these three factors. Based on the numbers of children
of particular ages using specific different types of care, positive caregiving
was estimated to be of poor quality for 8 percent of children under 3 years
in the United States, fair quality for 53 percent, good quality for 30 percent,
and excellent quality for 9 percent. These distributions suggested to the
investigators that care is neither outstanding nor terrible, but plenty
of room for improvement [remains].

The quality of child care in the United States also can be estimated based
on reports of structural and caregiver characteristics. Drawing on empirical
research and advice from professionals in the field, organizations such as
the American Academy of Pediatrics and the American Public Health Association
(1992) have established age-based guidelines for group size and child:adult
ratio. For example, the recommendations for child:adult ratios are 3:1 for
children from birth to 24 months, 4:1 for children from 25 to 30 months,
5:1 for children from 31 to 35 months, 7:1 for 3-year-olds, and 8:1 for
4-year-olds.

Table 10 lists regulations for child:adult
ratio and group size for each of the 50 states as compiled by the Center
for Career Development in Early Care and Education (1999). It is clear that
very few states have regulations as strict as those recommended by professional
organizations. For example, only three states have the recommended 3:1 ratio
for infants, and only one state has the recommended 3:1 ratios for 18-month-olds.
Two states have ratios consistent with the recommended 5:1 ratio for 3-year-olds.
Some states are at substantial odds with the recommended standards. For example,
eight states have child:adult ratios of 6:1 for infants. There is a similar
failure to meet recommended group size standards, with 20 states having no
regulations pertaining to group size.

Another way of estimating the quality of care in the United States is to
consider reports of structural and caregiver characteristics. One nationally
representative survey, the Profile of Child Care Settings (Kisker, Hofferth,
Phillips, and Farquhar, 1991), obtained this information in 1990 from child
care centers, early education programs, and licensed child care homes. According
to the Profile, the average child:adult ratio was 4:1 for infants under 1
year of age, 6:1 for 1-year-olds, and 10:1 for preschoolers. This report
indicates that the average center and child care home in 1990 did not meet
standards for child:adult ratios that have been linked to higher quality.
In contrast, the Profile of Child Care Settings found that caregivers tended
to be well educated and to have specialized training pertaining to children.
Nearly half of all teachers reported that they had completed college (47
percent) and an additional 13 percent reported a two-year degree. Most of
the remaining teachers had a Child Development Associate (CDA) (3)credential
(12 percent) or some college experience (15 percent). Only 14 percent did
not have any education beyond high school. Ninety percent of the teachers
in child care centers reported that they had received at least 10 hours of
in-service training.

The Profile survey found that regulated child care home providers had less
formal education and training than teachers in centers. Approximately 11
percent of regulated home providers reported that they had completed college;
34 percent had no schooling beyond high school. About two-thirds had received
specialized in-service training. This study represents the best available
information regarding structural and caregiver characteristics from nationally
representative samples. The survey is dated, however, in that the data were
collected in 1990, so the reports may not reflect current structural and
caregiver characteristics.

Published reports from two additional national surveys are less useful for
this issue. The National Child Care Survey,1990, and the National Household
Education Survey, 1995, collected information from parents regarding child:adult
ratios and caregiver training. The published reports from these surveys (Hofferth
et al., 1991; Hofferth et al., 1998), however, did not present ratio and
group size information separately by childrens age. As a result, it
is not possible to use the reports to evaluate the percentage of child care
settings that meet (or fail to meet) standards for infants, toddlers, and
preschoolers that are set differently. A second limitation of these reports
is that parents may not be accurate respondents of these quality parameters.

A third source of evidence pertaining to structural and caregiver characteristics
is the NICHD Study of Early Child Care (NICHD Early Child Care Research Network,
1999a). In that study, child:adult ratios were observed at regular intervals
and caregivers reported their educational background and specialized training.
The percentage of center classrooms that met the AAP and APHA recommendations
for child:adult ratio and group size is shown on
Table 12. Also shown are the percentage
of classrooms in which caregivers had at least some college and specialized
training. As indicated, 36 percent of the infant classrooms were observed
to have the recommended child:adult ratios of 3:1. Fifty-six percent of
caregivers in infant classrooms had received specialized training during
the preceding year; 65 percent of infant caregivers had some college courses.
Proportions were similar for toddler care (the 15- and 24-month-olds). When
compared to figures reported in the Profile of Child Care Settings, the NICHD
figures suggest that there has been some decline in the educational background
and training of child care staff during the 1990s.

The decrease in caregiver education and training may be related to the generally
low wages in the child care field (see Figure 3).

In 1997, child care teachers averaged $7.50$10.85 per hour, or
$13,125$18,988 per year, when they were employed for a 35-hour week
and a 50-week year. Wages for assistant teachers were $6.00 to $7.00 an hour
(or $10,500$12,250 per year). Figure 1 shows salaries
for lower-paid and higher-paid child care workers relative to the median
salaries of women 25+ by level of education for both 1992 and 1997. The figure
shows the low salaries of child care workers relative to other occupations
and indicates that there has not been any improvement in terms of the relative
salaries over the 19921997 time period for most levels of education.
While high school graduates who were child care teachers or assistants could
only earn between 73 and 85 percent of the salaries they might expect to
receive elsewhere, the relative salaries were far lower relative to the median
for women with more schooling. A child care teacher with a B.A. degree could
expect to earn between 52 and 75 percent of the median salaries across all
occupations. Current child care salaries are not consistent with attracting
and keeping providers who have the level of education and training that research
suggests is needed to structure emotionally supportive and cognitively
stimulating learning environments.

The generally low salaries earned by child care staff also appear to be a
factor contributing to high staff turnover in the child care field (see
Figure 4).

In 1997, 27 percent of teachers and 39 percent of assistants left their jobs
during the previous year (Figure 5 and Whitebook, Howes,
and Phillips, 1998).

Market failure is defined as a a situation in which a market left on
its own fails to allocate resources efficiently (Mankiw, 1998, p. 10).
Wherever market failure exists, public sector intervention may improve the
performance of that sector of the economy. In the child care sector, market
failure stems from two sources: lack of information and the existence of
externalities (effects beyond the primary consumers). Regarding the first,
a major problem is the absence of information on the part of parents, including
information on the quality of child care, sometimes on the availability of
care, and often on the net costs of alternative arrangements. Related to
this lack of information is the difficulty in capturing process quality by
measuring observable differences in structural quality. Even information
on the structural quality differences is not easily obtained a priori, and
the cost of acquiring information can be high.

One difficulty in providing information to parents is that much of this market
is made up of small providers. Parents may know something about the child
care used by their neighbors, but very little about other types or providers
of care. Parents report being unsure about how to go about evaluating child
care quality. Child care convenience also is of considerable concern to parents
limiting their search to care in particular small geographical areas. This
way of thinking about market failure is quite similar to that of medical
providers. The problem may be particularly acute for lower-income families
and for families who need care for evening or weekend employment (Vandell,
1998).

The second major cause of market failure is the existence of externalities.
The benefits of quality care accrue not just to the parent(s) but also to
the child and to society more generally. Parents may take all or part of
the benefit to their child into account, but not benefits that are external
to the family. Such benefits include lower costs for subsequent schooling
(reduced probability of grade retention and special education, for example),
future reductions in crime, increased productivity that results in higher
productivity for others, payment of higher taxes, and possibly lower costs
for social services. Improving child care quality may affect grade school
classrooms by increasing the proportion of children in the class who have
strong language and cognitive skills. By the same token, poor-quality child
care may undermine grade school classrooms by increasing the numbers of children
with academic and social deficits. Unsafe and unhealthy child care may result
in reduced productivity for others, when parents are absent from their jobs,
caring for injured or ill children. Adding these benefits to the parents
demand for higher-quality care should shift the demand curve for quality
care to the right (that is, increase demand for higher-quality care at every
price).

There may also be a third cause of market failure, an imperfect capital market.
Parents of young children tend to have low incomes relative to their permanent
income, but may face borrowing constraints that reduce their ability to pay
for high-quality care.

Justification for government intervention may also be based on distributional
or equality-of-opportunity goals. This may be especially relevant today,
in view of the requirement that most low-income single parents work. The
core argument here is that if high-quality child care can provide gains in
cognitive ability, school readiness, and social behavior, children in low-income
families should be given an opportunity to benefit from such experiences
just as high-income children benefit. Parents with limited earnings do not
have the private means to purchase high-quality child care for their children.
Government subsidies are necessary if equal opportunity for high-quality
care is to be afforded children in low-income families. The other side of
this argument is that if subsidies are not provided, parents with limited
incomes will use poor-quality care, including multiple arrangements, which
may be detrimental to the safety of their children, may increase family stress,
and may result in children with reduced opportunities. A subsidy (or direct
provision of care) for children in low-income families could also complement
the Earned Income Tax Credit and serve as an employment-related income subsidy
(see Council of Economic Advisers, 1997).

There are additional issues regarding availability of child care for families
with very low incomes and/or unusual and nonflexible hours of work. According
to several studies:

The structure of low-wage work and its lack of fit with the structure
of more formal child care options restricts the access of low-income families
to child care centers and many family day care homes. Data from the National
Child Care Survey indicate that one-third of working-poor mothers (incomes
below poverty) and more than one-fourth of working-class mothers (incomes
above poverty but below $25,000) worked weekends (Hofferth, 1995).

Yet only 10 percent of centers and 6 percent of family day care homes reported
providing weekend care. Almost half of working-poor parents worked on a rotating
or changing schedule, further restricting these families child care
options to more flexible arrangements made with relatives, friends, and
neighbors.

The features of low-wage work appear to promote reliance on multiple providers
as a way of patching together child care to cover parents nonstandard
and shifting work hours (Siegel and Loman, 1991). Meyers added that irregular
and unpredictable work schedules led to disruptions in child care for the
families in her study of the California GAIN program (Meyers, 1993). Deborah
Phillips wrote (1995)

In sum, when selecting child care, many working-poor and low-income
families must choose from a seriously constrained set of options. They face
a set of obstacles that derive primarily from the structure of low-wage jobs
and from the meager incomes that these jobs provide. Their low incomes enable
them to afford only free care by relatives and friends or very inexpensive
care; their nonstandard and often rotating work hours restrict them to
arrangements with flexible and weekend or evening hours of operation. These
factors may also lead to greater reliance on multiple providers and expose
young children to shifting child care arrangements.

This lack of stability and frequent changing is itself a measure of poor
quality of care.(3)

The market failure components argue for government intervention in improving
child care. They all lead the authors of this report to believe that the
demand for high-quality care is too low. And because demand is too low,
compensation is too low, resulting in better-trained providers tending to
seek employment in other spheres. This results in a decline in quality unless
intervention occurs. Intervention can take many forms.

The arguments behind the need for a role for government (including subsidies
for child care) is quite similar to those for primary schooling. Traditionally,
the amount of schooling provided has heavily depended on the public sector.
For children up to the age of 16, or older in some states, schooling is
mandatory, and is provided by the public sector. In the cases of elementary
and secondary education, public colleges and universities, the price charged
tends to be far below the marginal cost of schooling. Evaluation of the
appropriate level of public investment in education requires an analysis
of all returns to schooling, including nonmarket and external effects. For
example, greater education may lead to social cohesion and may enable one
to use new technologies; it may reduce the probability of criminal acts,
reduce the probability of application and receipt of transfers, and it may
increase savings rates. (For more on this see Wolfe and Zuvekas, 1997 and
Michael, 1982.)

Many of the benefits of child care are like those of primary schooling, because
child care is early childhood education. These early childhood educational
experiences affect childrens readiness for primary schooling in the
same way that primary schooling affects childrens readiness for secondary
schooling. In both cases many benefits are external to the child and family.
The community at large would benefit from the cognitive, language, and behavioral
competencies that are associated with higher-quality child care. The argument
for equality of opportunity is similar as well.

A high-quality child care system also is needed if welfare reform is to succeed.
The recent change in welfare policy, establishing work requirements, means
that more parents, particularly single parents, are working, because work
is their only potential source of income. Requiring work means that more
parents must find child care for their children. Given this increase in demand,
the issue of child care quality becomes even more important. Unfortunately,
as described in earlier sections, much of the child care in the United States
is not of high quality. Over 60 percent of children under the age of 3 are
receiving care in which positive caregiving is not characteristic. Only 10
percent are in care settings that are described as excellent.

A wide variety of approaches might be used to improve child care.
Figure 7 provides a path model that attempts to identify
the various links between interventions and quality, taking into account
parents resources.

Most of the interventions would be included in the elements of the left column.
These include the provision of information, licensing requirements, placement
activities, subsidies to compensate child care workers, training programs
for providers, tuition subsidies for students who enroll in early childhood
education, increased tax credits to cover the cost of care for lower- to
middle-income families, incentive payments to individual teachers and assistants
who remain in the same center for a minimum of 34 years, and even direct
provision of care. In the longer run, we need research to help better identify
those factors that best improve the quality of child care. In essence, we
need better understanding of the production of high-quality care, which may
differ for children of different backgrounds.

The minimum roles for the public sector are as providers of information on
available slots, hours of operation, structural quality features, costs of
care and education, and training of personnel. The government might also
establish a certification program to certify providers who met certain
requirements. Minimum standards need to be strengthened in many states.
Incentives might be offered to providers who meet certain requirements. Other
government activities to increase the availability of high-quality care include
operation of training programs and covering the cost of instructors and
facilities for these programs. Information on the successful completion of
such programs could be disseminated by the public sector as part of its
information activities.

A more ambitious role designed to increase the pool of well-qualified individuals
who enter (and remain) in the field of early childhood education would be
some form of tuition subsidy for those willing to major in this field. There
is a long tradition of such programs when shortages are feared; examples
include nursing education and medical school. An alternative might be a college
loan forgiveness program based on years spent as a child care provider following
college, or Associate degree completion. Another approach to increasing the
pool of qualified providers is to raise salaries. This seems especially important
given the relatively low salaries in child care compared to other occupations
(see Figure 1 and the discussion of the
figure above). Such increases might result from increased
information to parents, tax credits to parents, and the expansion of subsidy
programs or direct payment to providers by the public sector. An innovative
program might reward the stability of providers by paying a bonus after some
specified period of years.

Current programs to improve child care quality exist and might be replicated
or expanded. For example, a broad-based community initiative in North Carolina
(Smart Start) has been successful in improving child care quality (Bryant,
Maxwell, and Burchinal, 1999). This initiative, established by the governor
of North Carolina in 1993, is a partnership between state government, local
communities, service providers, and families. Twelve county partnerships
were initially selected based on competitive review to receive funds for
new and improved child care services. Data to evaluate the effectiveness
of the initiative were obtained in 1994 and 1996 from over 180 child care
centers in 12 counties. Local quality improvement activities (in 1996) were
distributed as follows: training workshops (83 percent), funds to attend
training activities (53 percent), on-site consultation or technical assistance
(58 percent), higher child care subsidy rates (35 percent), increased subsidies
for meeting higher standards (29 percent), funds to improve quality by purchasing
new equipment (70 percent), funds to improve quality by purchasing new
educational materials (63 percent), funds to achieve higher licensing level
(26 percent), funds to achieve national accreditation (13 percent), funds
to improve services for children with disabilities (11 percent), teacher
substitute pool (20 percent), transportation services (18 percent), lending
library (51 percent), and provider compensation programs (35 percent). The
mean number of improvement activities per center was 5.3 in 1994 and 5.8
in 1996, with a range of 0 to 14 activities each year. In both years, ECERS
scores were significantly related to the number of local quality improvement
activities in which individual centers participated. In addition, process
quality was significantly higher in 1996 than in 1994. Only 14 percent of
centers were rated as good quality in 1994. In 1996, this figure was 25 percent.
Participation in the Smart Start initiative also was related to a significant
increase in the percentage of centers that obtained the higher-level Associate
of Arts licensure credential.

Other efforts to improve quality might be to mandate certain minimum
requirements. These can take the form of reducing child:adult ratios, reducing
group sizes, establishing and enforcing safety regulations, and education
and training. An example of such regulations is a model standard that applies
to small family home caregivers. The National Health and Safety Performance
Standard (American Public Health Association and American Academy of Pediatrics,
1992) states that one small family caregiver who does not have an assistant
shall not care for more than six children, including no more than two
children under age 2. These numbers include the caregivers own children
under the age of six. If any child under age 3 is in care, there shall be
no more than four children, including the caregivers own children under
the age of six. If only children under age 2 are in care, there shall be
no more than three children, including those of the caregiver (Chapter
1, Staffing).

We also have training programs for providers of child care. The Department
of Labor, Bureau of Apprenticeship and Training, West Virginia Child Care
Development Specialist Registered Apprenticeship Program offers child care
apprentices 4,000 hours of supervised on-the-job training and 300 hours of
classroom instruction. The child care providers earn their salaries while
they are in the program and receive incremental wage increases as their skill,
ability, and knowledge increase. The DOL reports that employers report almost
no turnover among child care providers and that providers remain highly satisfied
with their careers
(www.dol.gov/dol/wb/public/childcare/child3.pdf).

Private employers may sometimes directly or indirectly provide resource and
referral services. Some employers contract with private agencies to assist
employees in learning about the range of child care options. The government
could encourage such activities by providing subsidies or tax credits to
firms if they provide such assistance. An example of this is the program
at the Virginia Mason Medical Center which offers child/family resource and
referral services.

Recent reports suggest that although some federal funds are available to
improve access to higher-quality care among lower-income families, some states
have not made these funds available or have set up programs that result in
low take-up rates. According to Access to Child Care for Low-Income
Working Families released in October 1999, 1.5 million children of
14.7 million (about 10 percent) in low-income households were receiving child
care subsidies. The major source of funds is the Child Care and Development
Fund (CCDF), a federal program that provides funds to states to subsidize
child care. According to federal law, children living in families with incomes
up to 85 percent of median income in the state could be eligible, but states
have set lower limits (http://www.acf.dhhs.gov/news/ccreport.htm). The levels
set and the take-up rates differ across states. The report details coverage
in each state and take-up rates. Expanding eligibility to the federal maximum
level and/or encouraging take-up of the existing subsidies through outreach
are ways to increase the demand for high-quality care.

This evidence indicates that families do respond to available subsidies.
The profile of arrangements used by these low-income parents is strikingly
different from that used by all low-income families. Siegel and Loman (1991)
found, as well, that AFDC families in Illinois showed different distributions
of child care use based on whether they received a child care subsidy and
which subsidy they received. Families receiving a child care benefit that
reimbursed them for their child care costs 30 to 60 days after they had incurred
these costs were discouraged from using child care options they could not
afford with their disposable income. Their patterns of use were similar to
those of unsubsidized, low-income families. In contrast, families who received
subsidies through programs that either subsidized providers directly or enabled
the families to pay providers when fees were due showed substantially higher
rates of reliance on center-based and formal family day care arrangements.

Subsidies can help low-income families gain access to the same range of quality
options that are available to higher-income families. The Urban Institutes
survey of resource and referral agencies in six communities provides evidence
that the quality of care received by subsidized children was as high as that
for higher income, fee-paying children, as perceived by resource and referral
staff (Phillips, 1995).

Another approach that could be combined with subsidies for very young children
would be to provide universal coverage for child care (or coverage for children
whose parents worked more than 20 hours per week) for pre-school-age children.
Such a program could expand existing prekindergarten programs to a full day
and include after-school care. These programs could be established for 3-
and 4-year-olds through a combination of direct provision through a local
school district, existing community-based programs, and vouchers that would
be accepted by certified providers. Part of the costs of this care would
be offset by eliminating tax credits and current government subsidies for
3- and 4-year-olds. States and local communities would decide on the details
of the provision of care, and financing would be shared across levels of
government. Part of a coordinated, high-quality child care system for toddlers
also might include community- and school-based centers and family day care
networks. Because of the necessary low child:adult ratios (and their attendant
expense), part of a coordinated child care policy for infants might include
vouchers that would allow a parent to stay home and care for the infant during
the first year.

Assessment of the Cost of Improving Quality

As we suggested, analyses that shed light on the developmental benefits of
child care characteristics for children is an important element of the answer
to our question. A related task involves determining the levels of investment
necessary to achieve improved quality. Although this topic has not received
the same level of attention in the literature as the overall relationship
between quality of care and child outcomes, several studies consider the
financial costs of increasing structural measures of quality. Though subject
to limitations that affect the extent to which one may apply these findings
to the current system of child care, this research provides useful information
on the relationship between the quality of child care and cost.

The U.S. General Accounting Office (GAO, 1990) report and Powell and
Cosgroves (1992) summary of and addendum to this GAO research include
estimated cost functions for the provision of child care as well as a model
of the factors that affect wages of care providers. The modeled cost function
allows the authors to examine the direct influences of input prices; center
characteristics, including structural measures of quality; and geographical
location on center total variable cost. This use of multiple regression analysis
allows the authors to estimate the effect of changing such factors as the
child-adult ratio on center total costs, after controlling for other relevant
factors such as group size, location, and average education of providers.
By also modeling the elements of wage determination, the authors capture
the indirect effect of changes in child care characteristics on the wages
of providers. The results from both models are then combined to examine direct
and indirect effects of quality changes on total variable costs.

Data on child care centers from a 1989 GAO survey of 265 early childhood
education centers accredited by the National Associate for the Education
of Young Children (NAEYC) were used in both
studies.(4) The survey, administered to
program directors via questionnaire, included questions of center
characteristics, costs, value of in-kind donations received, staff
characteristics and compensation. The survey includes several structural
measures that allow the authors to estimate the costs associated with changing
the following quality measures: the average number of children per teaching
staff member; average number of children in groups of four-year-olds; average
education of staff in years; average experience of staff in years; and the
staff turnover rate.(5)

The authors find statistically significant relationships between center total
cost and structural measures of child care quality. For the adult-child ratio,
they find that an improvement in the quality of care achieved by decreasing
the average ratio by one, for example from 11:1 to 10:1, is associated with
increased costs of roughly 4.5 percent. The authors note that the average
center in their data, one with 50 children and an annual per child cost of
$6,500, which reduces the child-to-staff ratio from 11:1 to 10:1, faces an
increase in annual cost per child of
$306.(6) A related measure, average group
size, had a small but statistically insignificant effect on total costs.

Changes in cost resulting from improving staff education and experience are
estimated using the estimated cost and wage functions to capture total direct
and indirect effects. The authors find that a one-year increase in average
education of the teaching staff is statistically significantly associated
with a 3.4 percent increase in total costs, which includes a 5.8 percent
increase in wages. Similarly, increasing average teacher experience by one
year is significantly associated with a reduction in center total costs of
0.6 percent, including an estimated increase in wages of 2.3 percent. This
implies that increasing staff experience is associated with an increase in
quality as well as a slight reduction in average center total costs. There
is also evidence of a relationship between turnover rates and total
coststhe departure of an additional 10 percent of the centers
teaching staff increases costs by 6.8 percent.

These studies have several limitations. First, they rely on data that are
more than ten years old. If the relationships estimated in their model have
changed since 1989, these estimates will differ from what we would expect
to find using current data. Changes in quality made now may affect total
costs in a different manner.

Also, the data include only accredited centers. If these centers have cost
functions that systematically differ from unaccredited centers, the estimated
results will not apply to those centers. If, for example, one is most concerned
with improving poor quality child care, and such care is more likely to be
found in unaccredited centers, these estimates may not provide an accurate
depiction of the costs of doing so. The sample also only includes data for
care of 4- and 5-year-old children. Because of differences in providing care
for other age groups, the relationship between improving quality and costs
for centers that provide care for other age groups may
vary.(7) Finally although the sample includes
data from many states, 70 percent of the centers surveyed were in the South
and the Midwest. The results therefore may not be nationally representative.

Helburn (1995) estimates a similar cost function using data collected as
a part of the Cost, Quality, and Child Outcomes in Care Centers (CQO) study.
The CQO study, conducted in 19931994, included data from 401 child
care centers (749 classrooms) in four states. The data, collected through
classroom observation and interviews with program directors, include information
on center characteristics, program quality and staff qualifications,
compensation, and turnover. Helburn estimates center total costs as a function
of staff wages at different education levels, hours of child care provided,
physical size of the center, volunteer hours, region of the country, for-profit
status, and quality measures.(8)

This research also indicates statistically significant relationships between
cost and quality. Increasing center quality by 25 percent (from mediocre
to good) is associated with increases in total variable costs of approximately
10 percent, or $346 per child per year. The authors define quality using
an index similar to the ECERS measure of quality of care. Using the ECERS
7-point scale, the mean value of this index in their sample is 4.0, which
ranks between fair and good. They estimate that the increase in total variable
costs associated with increasing the measure of quality by 25 percent to
5.0, a rating of good quality, will be approximately 10 percent. Given an
average size of 60 children per center, the increase in quality is expected
to result in an increase in costs of approximately $20,700 per
year.(9)

Helburn notes that this analysis assumes that wages are held constant during
the quality-changing process. The model specifically implies that wages for
particular quality-levels of staff (here measured by years of education)
are set in the labor market and centers pay the going wage. If, however,
high-quality centers pay higher than market wages to attract the most qualified
providers, or to increase productivity and/or lessen the chance of turnover
among existing workers, then estimated costs will understate true costs.

Although this study considers all types of centers, not accredited centers
only, it has similar limitations to the GAO and Powell and Cosgrove studies.
That is, the data used are not as recent as would be desired, and the results
from the four-state sample are not nationally representative.

Although all three studies have limitations, the estimates do provide information
on the nature of the relationship between child care costs and quality. As
such this research serves as a useful starting point for further consideration
of this topic. The importance of developing cost estimates suggests that
future work incorporating current and nationally representative data will
serve as an important source of information for evaluating public policy
strategies designed to improve the quality of child care. We have discovered
one likely source of such estimates in research currently being conducted
by Richard Brandon at the University of Washington and Lynn Kagan at Yale
University. The authors are developing a detailed simulation model to estimate
costs of improving child care using varied measures of quality. This research,
which the authors estimate will be completed by the fall of 2000, will provide
valuable additional information

None of these studies include the investment that is likely to be the least
expensive approach to improving quality: caregiver training, including in-service
training. There are a variety of training programs that have been offered
to formal and informal caregivers. The evidence above suggests that
better-trained caregivers give higher-quality care. We do not know enough
about the content or length of these programs to be able to definitively
discuss their cost. Curriculum and materials are readily available (see for
example the materials available from Teaching Strategies, Inc.) One program
suggests that a 12-workshop series would enhance caregivers skills
in areas that range from safety through cognitive development and communication
skills.

We conclude this report by returning to primary questions raised in the report:
Does child care quality matter? Does child care quality need to be improved,
and can it be improved? Is there an economic justification for public
intervention to improve the quality of child care, especially for children
from lower-income families? Our answer to each of these questions is
yes.

Does Child Care Quality Matter?

Our review of the research literature indicates that child care quality
matters at several levels. In terms of childrens everyday
experiences, children appear happier and more cognitively engaged in settings
in which caregivers are interacting with them positively and in settings
in which child:adult ratios are lower. There also is evidence of concurrent
relations between child care quality and childrens performance in other
settings. Children who attend higher-quality child care settings (measured
by caregiver behaviors, by physical facilities, by age-appropriate activities,
and by structural and caregiver characteristics) display better cognitive,
language, and social competencies on standardized tests and according to
parents, teachers, and observers. Finally, there is evidence that child care
quality is related to childrens subsequent competencies. The relationship
is more evident when cumulative measures of child care quality are analyzed,
rather than one-time assessments, and when quality and child outcome measures
have strong psychometric properties.

Does the Quality of Child Care Need to Be Improved, and Can It Be Improved?

Two general approaches to measuring child care quality were described in
this report. Process quality refers to childrens experiences in child
care settings. Some process measures focus specifically on caregivers
behaviors with children. Others include global ratings that incorporate physical
facilities and age-appropriate child activities as well as caregiver behavior
into their evaluation. Multisite studies suggest considerable need for
improvement of process quality in the United States. Although less than 10
percent of process quality has been categorized as inadequate
or poor, most settings have been characterized as only
fair or minimal. These observations indicate the
need for systematic efforts to improve a substantial portion of child care
in the United States.

A second way of measuring child care quality is in terms of structural and
caregiver characteristics, such as child:adult ratio, group sizes, teacher
formal education, and teacher specialized training. There is an extensive
research literature linking structural and caregiver characteristics to process
quality. A review of regulatory standards in the 50 states shows that few
states have adopted standards that are consistent with the recommendations
of professional organizations. Furthermore, reports from nationally
representative surveys indicate that average group sizes and ratios exceed
recommended standards. Recent evidence suggests a decline in the educational
background of staff during the 1990s, perhaps as a result of low wages. Thus,
it appears that child care structural and caregiver characteristics are in
need of improvement. They can be improved if additional resources are allocated.
This could occur through a combination of increased subsidies for care,
especially to low-income families; federal standards and/or increased state
standards for both physical settings and caregiver training and child:staff
ratios, improved information to parents on the quality of providers, and/or
direct provision or expansion of child care in schools.

Is There an Economic Justification for Public Intervention to Improve the
Quality of Child Care, Especially for Children from Lower-Income Families?

Market failure, the presence of externalities, and an argument for equality
of opportunity all call for public sector intervention in the child care
market. The primary form of market failure is the lack of information for
parents regarding quality of care which is tied to the difficulty in measuring
quality, the lack of availability of high quality care, and the need for
child care for irregular hours such as weekend and late shifts.

Benefits of quality child care accrue to other members of society, including
all children in schools with children who had child care; taxpayers, who
are likely to save in costs of future schooling by reduction in special education
and grade retention; employers, who benefit from more productive employees;
and citizens, who gain in terms of future reductions in crime and use of
transfer programs. Subsidizing child care for low-income families is also
consistent with the goals of the 1996 welfare reform and an ideology that
wishes to encourage and reward work. Finally, to the extent that high-quality
child care provides benefits to children and their families, there is an
argument for providing equal opportunity for such programs to children in
low-income families.

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Blau, D. M. 1999a. Does Nonrandom Assignment of Children to Child Care
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for High Risk African American Students at Middle Adolescence: Positive Effects
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80-30282. Washington, DC: U.S. Department of Health and Human Services.

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Centers: Technical Report. Denver, CO: Dept of Economics, Center for
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1) The authors gratefully thank the following for their
contributions to this paper: Josephine Chung, Kim Pierce, Scott Scriver,
and Elisabeth Boehnen for their research assistance and Dawn Duren, Jan
Blakeslee, Elizabeth Evanson for their editorial and typing assistance.

2) The NHES survey included an early childhood program
participation component in its 1995 survey. Parents of 14,000 children from
birth through third grade were asked about their use of a wide variety of
childcare and early education arrangements.
http://nces.ed.gov/nhes/

3) According to several studies, low-income families
use more of certain types of child care and less of others than do families
with more income or more education (see Figure 6).

According to the study by the National Academy (Phillips, 1995) low-income
families are more likely to rely on relatives and less likely to rely
on center-based arrangements. . . Grandparents are an especially prominent
source of child care for low-income, preschool-age children: 17 percent are
cared for mainly by grandparents; 29 percent get some care from a grandparent.
The child care arrangements of low-income families also vary greatly by household
type and parental employment status. . . Single employed mothers rely to
a much greater extent on non-relative arrangements (notably family day care
homes and centers) than do other types of low-income families. In addition,
among low-income families, about 24 percent of children under age 5 are in
more than one supplemental arrangement on a regular basis (Brayfield et al.,
1993). Reliance on multiple arrangements varies, however, from 14 percent
of low-income preschoolers with two parents to 31 percent of those in
single-mother families and 45 percent of those in employed, single-mother
families(Phillips, 1995, Chapter 2).

Connelly and Kimmel (2000) use a merged sample from the 1992 and 1993 SIPP
panels which include child care questions from June through December 1994.
They examine the choice of child care of full-time vs. part-time employed
mothers, married and single. Table 13 shows
their prediction, by marital status, of the marginal effects of the included
variables on the probability of choosing among the 3 modes of child care
for single employed mothers. The first panel uses a single predicted price
for child care and the second includes three predicted prices of care. For
single mothers, the predicted conditional probability of full-time employment
is a significant predictor of child care. As has been suggested by earlier
research, single mothers who are working full-time are more likely to use
center-based care. This also leads to the conclusion that as more mothers
enter full-time employment after leaving welfare, the utilization of center-based
care over other types of care will increase. The reported results also show
that women with more education are more likely to use center-based care or
home-based care and that women on AFDC who receive more dollars are somewhat
more likely to use center-based care and less likely to use relative care.
Somewhat surprisingly, single mothers with higher predicted wages appear
more likely to use relative care or home-based care than center care. The
authors explain this by hypothesizing that higher-wage jobs are more likely
to be positions that require more flexibility than center care can provide
in terms of pick-up and drop-off times and the care of sick children.

5) The other variables included in the model are average
hourly wages for teachers and aids; rent; cost of other supplies and services
per child; indicators for whether a center is for-profit, serves infants,
serves children with disabilities, has operated for less than two years;
and geographic location.

6) These estimates are expressed in current dollars.
The original estimates in 1988 dollars are $4,500 and $207, respectively.

7) The authors do control for centers that provide
infant care, but cost structures would nevertheless be expected to differ,
for example, in infant-care centers that do not provide care to 4- and
5-year-olds.

8) The relationship between structural measures of
quality and total variable costs are also tested, but there is no evidence
of statistically significant relationships. The authors note that their index
measure of quality may be a theoretically superior measure insofar as the
structural characteristics capture only a portion of the true
measure of quality. They argue that this is the case if the unobserved center
quality characteristics are correlated with other independent variables.

9) These estimates are expressed in current dollars.
The original estimates in 1994 dollars are $300 and $18,000 respectively.